AI on the Buyside: How to Prepare for the Algorithmic Investor

Dear IR Professional, You get it, AI is the new hype.

We've all been reading up, studying and comparing notes on the how. How can we use AI in IR? How can we make our lives more efficient? How can we use AI in our business. It's all great, but it's all focused on us. We've been so preoccupied with how we can use AI to analyze market sentiment, find new shareholders, or just make our lives a little easier, that we're overlooking an important part of our job. The investors! As with any tool in our lives, we're busy playing around with it and trying to make the most of it, but we're overlooking the fact that we're not the only ones doing it. So what happens when AI is in the hands of investors?

I remember the first time this really hit me. I was on an earnings call, and this analyst, someone I knew, asked a question that was just… off. It was hyper-specific - something about a tiny financial variance in a non-core metric over a really weird time frame. There was no emotion, no context, just a raw, almost robotic question based purely on data. In that moment, it hit me: I was talking to a brilliant human being, but one who was almost certainly being fed information, or even guided, by a machine.

The truth is that the buy side has been playing with AI for some time now, and their game is getting more sophisticated every day. The whole idea that the buy-side analyst is basing his thesis on a gut feeling and a deep dive? That’s still the case, but now that gut feeling is backed up by data points that no human could ever process on their own. Our job, our new mission, is to understand this new breed of "algorithmic investor" and figure out how to speak their language.

The New Buyside Toolkit: What's Really Going On

To get a handle on this, let's break down the new tools they're using. The modern buy-side firm is no longer just reading your press releases and listening in on your phone calls. They do so much more.

First, there's the screening. Imagine this: A fund manager has a mandate, such as "look for companies with this particular growth pattern and this keyword in their press releases" AI can scan thousands of companies in minutes, a task that would take a human a lifetime. If your company's story or financial data isn't presented clearly and consistently in a way a machine can understand, you may not even get past that first filter. You will simply be skipped over.

Then there’s the use of alternative data and sentiment analysis. In the past, opinions about your company were based on official reports and analysts' statements. And now? They use AI to scrape millions of data points from everywhere- chatter on social media, headlines in the news, customer reviews on sites like Yelp, even employee reviews on Glassdoor. This gives them a real-time, unfiltered view of what people actually think about your company. This "shadow analysis" can make a perfectly polished press release completely superfluous.

Finally, they use AI for predictive analytics and due diligence. The models don't just look at what has happened, they try to predict what will come next. They analyze your historical data and the industry as a whole, looking for trends and correlations that a human might never see. In due diligence, an AI can go through every single regulatory filing, earnings transcript, and corporate report and pinpoint risks or opportunities within minutes- a task that would take an entire team of analysts weeks to complete. It's no longer just about your forecast, it's about their model’s forecast, which they trust because it’s objective.

Your Digital Footprint: Preparing for the Robots

So what should we do? We can't control their tools, but we can certainly make sure that our company’s digital footprint is a clean, well-marked trail that both humans and machines can follow.

Accessibility of data is an important point. Your IR website should not just be a place where old PDFs are stored. It needs to be a data paradise. Our documents should be machine-readable, not just fuzzy image scans. Our data tables should be structured and consistent from quarter to quarter. A machine can't do anything with something that constantly changes its format. Think of yourself as a data librarian, making sure everything is easy to find and understand.

Consistency is key. It’s not just about getting your numbers right. AI models thrive on consistent language. Do you always use the same words to describe your business segments? Do your ESG metrics have the same names from year to year? Inconsistent language or fluctuating numbers can confuse a model and lead to your company being labeled as - well - messy. Make sure your messaging is bulletproof and your data is consistent across all public documents.

Look beyond the press release. While our official reports are important, we need to start paying more attention to our overall digital presence. We should actively monitor what is being said about us online. Is there a rumor doing the rounds on social media? Are employee reviews accurate? We need to be aware of this "shadow data" and be prepared to address it because their models are already recording it.

The New Conversation: Preparing for the AI-Driven Question

The most tangible change for us is how our investor conversations are changing. We're still talking to a human, but that human is equipped with the insights of a machine.

The questions you get might feel different. They might be very specific, without human context. For example, "Your selling, general and administrative expenses as a percentage of revenue in Q3 2024 differed by 1.2% from your average over the last eight quarters. Can you explain that?" This is not a guess or a feeling, but a statistical anomaly found by a machine.

So how do you prepare for this situation? The days of simply going through your presentation slides are over. Your preparation needs to focus more on data. You need to be able to access and explain granular data points. You should try to anticipate the questions your own internal data models might raise.

But the real key is to respond to the data-driven question with a human, strategic answer. "That tiny discrepancy you noticed? You're right about that. It's a direct result of our investment in our new sales team in the EMEA region. We see this as one of the most important factors for future sales growth." This shows that you not only understand the data, but can also provide the crucial strategic context that the machine cannot. You are the bridge between the raw data and the compelling story.

The Bottom Line

Let's not fool ourselves. AI on the buy side is not a threat to our profession; it is simply the new normal. The IRO who understands this and adapts to it will not only survive, but also thrive. By ensuring that our company's digital footprint is clean, our data is consistent, and our communications are both strategic and data-aware, we can turn what seems like a big, intimidating challenge into a powerful competitive advantage. We are indispensable partners to both management and the buy-side, translating human strategies into algorithmic analysis and giving human context to a world full of data.

Have you already adopted your communication to be better understood by robots? This is an immensely interesting topic, I would love to hear about your progress!

Best, Muge

Your fellow IR Enthusiast!

Currently serving as the Director of Investor Relations and Sustainability at Galata Wind Enerji (GWIND.IS), Yücel brings a wealth of experience to the role, having begun her investor relations career in 2008 at Dogus Otomotiv (DOAS.IS). Her expertise in proactive strategies utilizing digital technology and AI, particularly in shareholder targeting, is instrumental in communicating Galata Wind's growth story. Traded on the Istanbul Stock Exchange, Galata Wind operates wind and solar farms in Turkey and is strategically expanding into Europe, targeting a capacity of over 1000 MW by 2030.

Yücel has recently published "The Investor Relations Playbook - Achieving Sustainable Success", a hands-on guidebook on investor relations operations with templates, checklists and how-to guides. The book is available in print in Turkish and in digital form in English.